ISI: PAM & ASK OVER BAND-LIMITED CHANNELS

Size: px
Start display at page:

Download "ISI: PAM & ASK OVER BAND-LIMITED CHANNELS"

Transcription

1 ISI: PAM & ASK OVER BAND-LIMITED CHANNELS PREPARATION... 2 what is ISI?... 2 to do before the lab... 3 what we will do... 3 EXPERIMENT... 3 Bessel pulseforms... 3 Bessel sequences and eye patterns... 5 Butterworth channel... 6 what have we discovered?... 7 postscript... 7 TUTORIAL QUESTIONS... 8 Further reading copyright robert radzyner 2003 Vol D3, ch 1, rev 1.1-1

2 ISI: PAM & ASK OVER BAND-LIMITED CHANNELS ACHIEVEMENTS: discover how to transmit digital data efficiently with minimum intersymbol interference (ISI) over bandwidth constrained channels. PREREQUISITES: refer to recommendations under "preparation" ADVANCED MODULES: BASEBAND CHANNEL FILTERS, LINE-CODE ENCODER, DECISION MAKER, DIGITAL UTILITIES SCOPE: availability of a digital or PC-based scope would be an advantage for eye pattern displays PREPARATION what is ISI? In the experiment D2-06 entitled PCM-TDM, and the Lab Sheet L-54 PAM and TDM we investigated the transmission of sampled signals using amplitude modulated pulses. In these experiments the pulses used as the carriers of the sampled values were narrow rectangular pulses produced with a TWIN PULSE GENERATOR. In that work pulse distortion was not an issue since there was ample bandwidth to pass the sharp transitions. In this experiment we explore how to deal with pulse amplitude modulated (PAM) signals when the pulse streams are transmitted over real channels that have finite bandwidth. The key issue is the interference caused by overlapping sidelobes and tails affecting neighbouring pulses. This is known variously as crosstalk and intersymbol interference (ISI). ISI is a concern not only when dealing with PAM carrying analog sample values, but also in digital communications. For example, minimizing ISI in quantized PAM such as ASK, QAM and PCM gives increased margin against errors caused by noise. This allows a greater density of discrete amplitude levels, hence a greater number of bits per symbol interval. In this experiment we investigate pulse shape characteristics that facilitate transmission over bandwidth limited systems without causing ISI. We will discover how pulses with finite transition times and trailing oscillations ( ringing ) can be interwoven in rapid succession without affecting their data payload. 2 D3

3 to do before the lab This experiment can be approached as a journey of discovery, hence the probing deeper may be more interesting later. However you should do a quick refresh of the material in experiment D2-06 and Lab Sheet L-54, which deal with PAM and TDM, as well as experiment D1-02 and Lab Sheet L-36 introducing eye patterns. A brief review of the TIMS Advanced Modules User Manual for the DECISION MAKER and LINE-CODE ENCODER modules should save time at the workbench. what we will do We will begin with a fairly detailed inspection of pulseforms produced with a Bessel filter and then observe how these can produce a signal that is free of ISI when adjacent pulses overlap. Next we investigate pulseforms generated with a Butterworth filter. Unlike the Bessel case, here we have pulses with several cycles of trailing oscillations. We shall discover a technique for protecting the information payload of a pulse when overlapping occurs. Eye pattern displays will be used to investigate the range of pulse rates that can be transmitted without ISI 1. In other experiments we show how pulse shapes are manipulated to achieve higher transmission rates. Bessel pulseforms EXPERIMENT In this section we generate a periodic repetition of an isolated Bessel pulse. T1 patch up the system in Figure 1, one module at a time, starting with the VCO (on-board switch SW2 to VCO mode), then LINE-CODE ENCODER M.CLK and B.CLK, divide by 8 in DIGITAL UTILITIES, B.CLK IN & B.CLK OUT in the DECISION MAKER (the on-board SW1 may be in any position). Tune the VCO near 8000 Hz. Note that the LINE- CODE ENCODER generates a frequency division by 4 at B.CLK OUT. OUT Figure 1: set-up for displaying isolated pulseform DC systems 1 although these demonstrations are modelled at baseband, the principles apply equally with carrier D3-3

4 T2 check that the B.CLK OUT of the DECISION MAKER is a train of TTL LO pulses (the trigger range of the monostable may depend on the VCO frequency if there is no output, alter the position of the decision point control on the front panel to enable the trigger circuit). The repetition rate should be the VCO frequency divided by 32. T3 measure and note the width of the pulse from B.CLK OUT of the DECISION MAKER. Observe that the width of this pulse is fixed and not affected by the VCO frequency. 2 T4 obtain erect pulses by connecting the DECISION MAKER B.CLK OUT to the TTL inverter in the DIGITAL UTILITIES. T5 connect the inverter output to the LINE-CODE ENCODER DATA input. Display both the input and the UNI-RZ output and compare their widths as you vary the VCO frequency. Our pulse generator is now ready. You may be wondering why the LINE-CODE ENCODER is needed. In T3 and T5 you will have noticed that while the input pulse width remains constant as the VCO frequency changes, the UNI-RZ pulse width does not it varies so that it is always half the period of the bit clock. This way we ensure that the excitation pulse has the correct width when comparing bandlimited sequences and the corresponding isolated pulse shape at a selected pulse frequency (we shall be using sequences generated with half pulse line codes). T6 set the front panel switch of the BASEBAND CHANNEL FILTERS to position 3 to select the Bessel filter, and the front panel toggle switch for DC coupling. T7 with UNI-RZ 3 pulses at the input, connect the filter output through the ADDER to allow for amplitude control and DC offset correction in the usual way. The output display should have the general appearance shown in Figure 2 (pulse amplitude is around 1.6 V). T8 remove any DC offset and measure the width of the output pulseform across its base (ie. at zero volts) 4. Figure 2: Bessel pulse and eye pattern (symbol width 367µs) 2 note that we shall not be using any other functions of the DECISION MAKER its role here is merely to serve as a monostable with suitable pulse width (a TWIN-PULSE GENERATOR would be an alternative, however the pulse width is too narrow). 3 we shall be using RZ-AMI for sequences. The Uni-RZ format is required for the generation of individual pulseform snapshots. The pulseform elements are the same in both formats. 4 you may find the RZ-AMI line code with eye pattern scope triggering better suited for precision DC offset adjustment.. 4 D3

5 Bessel sequences and eye patterns We will now generate and observe PAM sequences of Bessel pulses by patching up the model of Figure 3. As we are in a digital communications context, using discrete amplitude levels, this is amplitude shift keying (ASK). We will first display sequence snapshots, then eye patterns. T9 before inserting the SEQUENCE GENERATOR set the on-board dip switch SW-2 for a short sequence (both toggles UP). T10 patch up the model of Figure 3 5. SNAPSHOT SYNCH OUT DC Figure 3: set-up for eye pattern and snapshot displays The set-up is not greatly different to that in Figure 1: a SEQUENCE GENERATOR replaces the DIGITAL UTILITIES and DECISION MAKER subsystem. Remember to change the line code to RZ-AMI (note that a TTL LO generates a zero valued RZ- AMI output). 6 T11 trigger the scope with the SYNC output of the SEQUENCE GENERATOR to generate a snapshot display of the sequence before and after the filter. T12 starting with a pulse rate around 2000 Hz, compare the appearance of the input and output sequences, and verify that you are able to easily recognize the individual symbol values in the bandlimited output. T13 vary the pulse frequency over the range Hz and note any changes you observe, especially as the symbol interval is reduced. Record the highest pulse frequency that allows you to comfortably recognize the symbols. Examine the sequence snapshot display and observe that pulseforms overlap across adjacent symbol intervals as you increase frequency toward 3000 Hz, the overlap approaches 100%. Even with an overlap of up to 100%, the appearance of the waveform is regular and individual symbols have a consistent shape and amplitude. Consider how this occurs and whether this indicates absence of ISI (this question will be resolved in T15 and T16). 5 the new set-up can be assembled without disturbing the DIGITAL UTILITIES and DECISION MAKER set-up it will be needed again. The only change required is to move the LINE-CODE ENCODER DATA input lead from the TTL inverter output to the SEQUENCE GENERATOR output. 6 in this lab we are not concerned with the properties of RZ-AMI line coding. This pulse format has been chosen as a good vehicle for presenting the eye pattern demonstrations. D3-5

6 T14 change the scope settings to display the eye pattern (use the B.CLK signal as scope trigger). Note that this is a three level display (see Figure 2). Using the longest sequence (both toggles of the on-board DIP switch SW-2 DOWN) will generate more transitions for the eye pattern. T15 repeat the steps above, and note the maximum pulse frequency for which the eye remains fully open. Compare this with the maximum frequency you determined with the snapshot display. Note how, with a fully open eye pattern only three distinct amplitude levels occur at the centre of the pulse interval, even with adjacent pulses overlapping. T16 using the observations you recorded for isolated pulses, demonstrate how 100% overlap may occur without causing ISI at the critical point for sampling and decision. T17 increase the pulse frequency further, so that the inner envelopes of the eye pattern begin to close. Propose a measure of eye closure (as a percentage or in db units). Obtain the eye closure value at three or four pulse frequencies, and plot the result as a function of frequency. Are you surprised by the outcome? Butterworth channel T18 with the set-up unchanged 7, switch to the Butterworth filter of the BASEBAND CHANNEL FILTERS module (position 2 on front panel). You may need to re-adjust the amplitude and DC offset. T19 observe the eye pattern over a range of pulse frequencies as before, and measure eye opening and frequency for the best outcome. Note that unlike the Bessel case, the eye pattern deteriorates at frequencies below and above the optimum. Experience has shown that a better eye may be obtained with a slightly modified filter response. T20 connect the RC LPF in the UTILITIES module in cascade with the Butterworth filter and repeat the above. Note that the eye pattern is not symmetrical (see Figure 4). Figure 4: Butterworth-RC pulse and eye pattern (symbol width 480µs) 7 this saves a little set-up time. More importantly, this is a better path to the desired outcome. 6 D3

7 T21 with the pulse frequency set for the best eye you can obtain (with or without the RC LPF), return to the sequence snapshot mode (scope external trigger to SEQUENCE GENERATOR SYNCH output) and note whether you are able to clearly identify the amplitudes of the individual pulse elements. T22 again, with the pulse frequency unchanged, return to the pulseform mode (just move three leads: LINE-CODE ENCODER DATA input back to TTL inverter and scope trigger; filters input back to UNI-RZ line-code output). Observe the significant trailing oscillations spanning several periods of the pulse frequency (see Figure 4: spacing between cursors is 0.96ms). T23 measure the intervals between the first few zero crossings. Note the variation and compare with the period of the eye pattern. what have we discovered? From the zero crossing measurements on the Butterworth pulseform we find that a nice eye pattern - with zero or near zero ISI occurs when the interval between particular zero crossings is equal to the pulse transmission interval, i.e. the period of the eye pattern. To see how ISI is avoided in a situation with multiple overlap of pulses, try the following exercise. Trace the pulseform of Figure 4 onto a transparent sheet, lay it carefully on top of the original with an arbitrary lateral displacement other than a multiple of 0.48ms and sketch the sum (ensure that the time axes are precisely aligned). Then repeat this with a multiple of 0.48ms and note the difference. The exercise is more satisfying if three or more pulses are used (you can also subtract). The critical point to note is the generation of values that are made up of only one non-zero contribution one for each pulse in the summation. Indeed, by now you will have realized that this process is replicating the process taking place in the scope when you trigger for an eye pattern display. Observe how the sidelobes can be seen about the zero amplitude level in the eye pattern, and compare with the Bessel eye. 8 Thus, as you see, if the pulse stream is the summation of pulses with ideal zero crossings, there will be only one non-zero contribution at the point where the critical zero crossings occur. Hence, inspection of the pulse stream at these points will be free of interference by overlapping pulses. This idea was discovered by H. Nyquist in the 1920 s in telegraphy applications, and is known as Nyquist s First Criterion. It is the key to ISI-free digital communications over channels that have limited bandwidth. postscript Comparing your observations in this experiment, you may be left with the impression that the Bessel pulseform would be the preferred choice it allowed a significantly higher pulse rate than the Butterworth case (near 50% faster), and is not sensitive to 8 note that this is a benefit of using RZ-AMI input format for this demonstration. It comes about due to the frequent strings of zero values. D3-7

8 symbol frequency. Nevertheless, from the zero crossing spacing of the Butterworth pulseform, you may have been tempted to venture an eye pattern near 4200 pulses per second 9. Indeed, you would have been rewarded with a distinct eye, possibly around 70% open or better. Inspection of the Butterworth pulseform in Figure 4 indicates that an impediment to better performance at the higher pulse frequency is the initially sluggish risetime of the leading edge. In the experiment D3-02 entitled equalization for ISI we use a PHASE SHIFTER to reduce the attack time by introducing a precursor zero crossing. Thus equalized, this pulseform provides good ISI quality at frequencies around 30% higher than Bessel. An interesting conclusion: to get the most from your digital communication system when bandwidth is in limited supply, use smart analog pulseforms to represents the digital symbols. TUTORIAL QUESTIONS Q1 Give two examples of band-limited channels commonly used for digital communication. Also, give an example of a channel that is not bandlimited. Q2 Why are rectangular pulse shapes unsuitable for efficient digital communications over band-limited channels? Indicate your understanding of the term efficient in this context. Q3 Explain why a low-pass filter is needed in baseband digital communications receivers operating over wideband channels, i.e. channels with no bandwidth constraint (such channels are usually referred to as power limited ). Hint: think about matched filters. Q4 Describe how intersymbol interference (ISI) arises in PAM and ASK systems operating over band-limited channels. Q5 At the lab bench you re-discovered Nyquist s smart idea of exploiting zero crossings to deal with the unavoidable time spreading that comes about when working with channels of limited bandwidth. In this exercise we examine some basic theory that underpins Nyquist s scheme. (a) confirm to your satisfaction that the Fourier transform of the (two-sided) frequency domain function G(f) = G 0 over B f < B, and zero at other values of f is given by g(t) = 2G 0 B sinc(2bt) where f is in Hz and sinc(u) denotes sin(πu)/( πu). Verify that the value of g(0) is the area under G(f). 9 may require the VCO s HI range (front panel toggle switch) with a frequency division by 4 (DIGITAL UTILITIES module). 8 D3

9 (b) Sketch the graph of g(t) and note the placement and spacing of the zero crossings. (c) We now generate an ASK message y(t) using the sinc function in part (a) to represent the symbol pulseform 10, i.e. y(t) = Σ k A k sinc[2b(t k/t s )] where: A k represents 11 random binary amplitudes ±A 0 ( volt ) T s is the symbol period (sec) k is an integer representing the symbol index Note that this expression reflects the scenario we had in the lab, where we were free to set the pulse rate with the VCO, i.e. we could tune the VCO for the desired value of symbol interval T s. Let s do this here. An interesting possibility is to have T s = 1/(2B). Substitute this in the expression for y(t), and show that at values t m of t such that 2Bt m is an integer m, all the terms in the summation except one vanish, and y(t m ) = A m. Moreover, satisfy yourself that for non integer values of 2Bt, y(t) is the summation 12 of a large number of contributions. Compare this with your observations in the lab. Note that setting T s to integer multiples of 1/(2B) will also yield the same outcome, however this is of no practical interest since we will prefer to use the highest available symbol rate, i.e. two symbols per second per Hz of bandwidth. (d) It turns out that the bandwidth efficiency of two symbols per second per Hz in part (c) is the highest that can be achieved for band-limited PAM free of ISI. Many band-limited basic pulses with suitable zero crossings exist, however the product of zero crossing interval and bandwidth will be greater than 2. Thus, the sinc pulseform represents a theoretical benchmark for bandwidth efficiency for band-limited PAM and ASK free of ISI or information loss. Is it possible to prove this in a simple way? Here is an interesting demonstration. We consider the alternating ASK sequence, +A 0, -A 0, +A 0, -A 0, +A 0, -A 0, +A 0, -A 0, using any symbol pulseform with symbol interval T s. Show that this waveform has a line spectrum (i.e. a Fourier series). What is the frequency of 10 while the sinc function is unrealisable, practical approximations are readily generated. However, as will be seen in the experiment ISI: Pulse shaping for band-limited channels, some of its characteristics are undesirable for practical applications. 11 sometimes there is a stipulation that the A k s be uncorrelated. If correlation is present (e.g. through line-code encoding) the spectrum of y(t) will not be the same as the spectrum of the basic pulse; however, for this exercise, the only parameter of interest is the bandwidth, which is not affected. 12 students interested in the mathematical niceties might be tempted to examine the convergence (or otherwise) of even one such summation. If you are not happy with the behaviour of the sinc function, you could treat it as a limiting case of a vestigial symmetry Nyquist pulseform this is normally covered in most basic texts that include the Nyquist scheme. D3-9

10 the fundamental? We now consider the transmission of this message over a baseband channel with infinite attenuation above f c Hz. What is the minimum value of T s for which any component of the message can pass through the channel? This sequence is a member of the set of binary message sequences that may occur. We assert that if a channel of bandwidth slightly less than B = f c = 1/(2 T s ) Hz does not pass this message, then the minimum bandwidth needed for transmission without distortion or information loss is B = 1/(2 T s ). Mathematicians are generally more comfortable with this kind of argument than engineers what do you think? Q6 Imagine a student who has already completed an experiment with the DECISION MAKER but has not come across Nyquist eye patterns that you generated in this lab. Show your colleague how to position the trigger instants for a decision device so that interference from adjacent symbols is minimized. Further reading Most standard textbooks cover the basics of the Nyquist theory. For an excellent and particularly insightful presentation, look up Introduction to signal transmission by W.R. Bennett, if you are lucky enough to find a copy in your library (McGraw-Hill, 1970). 10 D3

EE 400L Communications. Laboratory Exercise #7 Digital Modulation

EE 400L Communications. Laboratory Exercise #7 Digital Modulation EE 400L Communications Laboratory Exercise #7 Digital Modulation Department of Electrical and Computer Engineering University of Nevada, at Las Vegas PREPARATION 1- ASK Amplitude shift keying - ASK - in

More information

DELTA MODULATION. PREPARATION principle of operation slope overload and granularity...124

DELTA MODULATION. PREPARATION principle of operation slope overload and granularity...124 DELTA MODULATION PREPARATION...122 principle of operation...122 block diagram...122 step size calculation...124 slope overload and granularity...124 slope overload...124 granular noise...125 noise and

More information

EE 460L University of Nevada, Las Vegas ECE Department

EE 460L University of Nevada, Las Vegas ECE Department EE 460L PREPARATION 1- ASK Amplitude shift keying - ASK - in the context of digital communications is a modulation process which imparts to a sinusoid two or more discrete amplitude levels. These are related

More information

EXPERIMENT 2: Frequency Shift Keying (FSK)

EXPERIMENT 2: Frequency Shift Keying (FSK) EXPERIMENT 2: Frequency Shift Keying (FSK) 1) OBJECTIVE Generation and demodulation of a frequency shift keyed (FSK) signal 2) PRELIMINARY DISCUSSION In FSK, the frequency of a carrier signal is modified

More information

Universitas Sumatera Utara

Universitas Sumatera Utara Amplitude Shift Keying & Frequency Shift Keying Aim: To generate and demodulate an amplitude shift keyed (ASK) signal and a binary FSK signal. Intro to Generation of ASK Amplitude shift keying - ASK -

More information

Experiment 2 Effects of Filtering

Experiment 2 Effects of Filtering Experiment 2 Effects of Filtering INTRODUCTION This experiment demonstrates the relationship between the time and frequency domains. A basic rule of thumb is that the wider the bandwidth allowed for the

More information

QUESTION BANK SUBJECT: DIGITAL COMMUNICATION (15EC61)

QUESTION BANK SUBJECT: DIGITAL COMMUNICATION (15EC61) QUESTION BANK SUBJECT: DIGITAL COMMUNICATION (15EC61) Module 1 1. Explain Digital communication system with a neat block diagram. 2. What are the differences between digital and analog communication systems?

More information

Handout 13: Intersymbol Interference

Handout 13: Intersymbol Interference ENGG 2310-B: Principles of Communication Systems 2018 19 First Term Handout 13: Intersymbol Interference Instructor: Wing-Kin Ma November 19, 2018 Suggested Reading: Chapter 8 of Simon Haykin and Michael

More information

SIGNALS AND SYSTEMS LABORATORY 13: Digital Communication

SIGNALS AND SYSTEMS LABORATORY 13: Digital Communication SIGNALS AND SYSTEMS LABORATORY 13: Digital Communication INTRODUCTION Digital Communication refers to the transmission of binary, or digital, information over analog channels. In this laboratory you will

More information

Experiment 1 Special signals characteristics and applications

Experiment 1 Special signals characteristics and applications Experiment 1 Special signals characteristics and applications Achievements in this experiment Time domain responses are discovered: step and impulse responses as paradigms for the characterization of system

More information

EE390 Final Exam Fall Term 2002 Friday, December 13, 2002

EE390 Final Exam Fall Term 2002 Friday, December 13, 2002 Name Page 1 of 11 EE390 Final Exam Fall Term 2002 Friday, December 13, 2002 Notes 1. This is a 2 hour exam, starting at 9:00 am and ending at 11:00 am. The exam is worth a total of 50 marks, broken down

More information

EE5713 : Advanced Digital Communications

EE5713 : Advanced Digital Communications EE573 : Advanced Digital Communications Week 4, 5: Inter Symbol Interference (ISI) Nyquist Criteria for ISI Pulse Shaping and Raised-Cosine Filter Eye Pattern Error Performance Degradation (On Board) Demodulation

More information

EE3723 : Digital Communications

EE3723 : Digital Communications EE3723 : Digital Communications Week 11, 12: Inter Symbol Interference (ISI) Nyquist Criteria for ISI Pulse Shaping and Raised-Cosine Filter Eye Pattern Equalization (On Board) 01-Jun-15 Muhammad Ali Jinnah

More information

Linear Time-Invariant Systems

Linear Time-Invariant Systems Linear Time-Invariant Systems Modules: Wideband True RMS Meter, Audio Oscillator, Utilities, Digital Utilities, Twin Pulse Generator, Tuneable LPF, 100-kHz Channel Filters, Phase Shifter, Quadrature Phase

More information

Lecture 3 Concepts for the Data Communications and Computer Interconnection

Lecture 3 Concepts for the Data Communications and Computer Interconnection Lecture 3 Concepts for the Data Communications and Computer Interconnection Aim: overview of existing methods and techniques Terms used: -Data entities conveying meaning (of information) -Signals data

More information

Time division multiplexing The block diagram for TDM is illustrated as shown in the figure

Time division multiplexing The block diagram for TDM is illustrated as shown in the figure CHAPTER 2 Syllabus: 1) Pulse amplitude modulation 2) TDM 3) Wave form coding techniques 4) PCM 5) Quantization noise and SNR 6) Robust quantization Pulse amplitude modulation In pulse amplitude modulation,

More information

DSBSC GENERATION. PREPARATION definition of a DSBSC viewing envelopes multi-tone message... 37

DSBSC GENERATION. PREPARATION definition of a DSBSC viewing envelopes multi-tone message... 37 DSBSC GENERATION PREPARATION... 34 definition of a DSBSC... 34 block diagram...36 viewing envelopes... 36 multi-tone message... 37 linear modulation...38 spectrum analysis... 38 EXPERIMENT... 38 the MULTIPLIER...

More information

Communication Systems Modelling

Communication Systems Modelling Communication Systems Modelling with Volume D2 Further & Advanced Digital Experiments Tim Hooper Communication Systems Modelling with Volume D2 Further & Advanced Digital Experiments Emona Instruments

More information

DIGITAL UTILITY SUB- SYSTEMS

DIGITAL UTILITY SUB- SYSTEMS DIGITAL UTILITY SUB- SYSTEMS INTRODUCTION... 138 bandpass filters... 138 digital delay... 139 digital divide-by-1, 2, 4, or 8... 140 digital divide-by-2, 3, 4... 140 digital divide-by-4... 141 digital

More information

Text Book: Simon Haykin & Michael Moher,

Text Book: Simon Haykin & Michael Moher, Qassim University College of Engineering Electrical Engineering Department Electronics and Communications Course: EE322 Digital Communications Prerequisite: EE320 Text Book: Simon Haykin & Michael Moher,

More information

PULSE SHAPING AND RECEIVE FILTERING

PULSE SHAPING AND RECEIVE FILTERING PULSE SHAPING AND RECEIVE FILTERING Pulse and Pulse Amplitude Modulated Message Spectrum Eye Diagram Nyquist Pulses Matched Filtering Matched, Nyquist Transmit and Receive Filter Combination adaptive components

More information

INTRODUCTION TO COMMUNICATION SYSTEMS LABORATORY IV. Binary Pulse Amplitude Modulation and Pulse Code Modulation

INTRODUCTION TO COMMUNICATION SYSTEMS LABORATORY IV. Binary Pulse Amplitude Modulation and Pulse Code Modulation INTRODUCTION TO COMMUNICATION SYSTEMS Introduction: LABORATORY IV Binary Pulse Amplitude Modulation and Pulse Code Modulation In this lab we will explore some of the elementary characteristics of binary

More information

YEDITEPE UNIVERSITY ENGINEERING FACULTY COMMUNICATION SYSTEMS LABORATORY EE 354 COMMUNICATION SYSTEMS

YEDITEPE UNIVERSITY ENGINEERING FACULTY COMMUNICATION SYSTEMS LABORATORY EE 354 COMMUNICATION SYSTEMS YEDITEPE UNIVERSITY ENGINEERING FACULTY COMMUNICATION SYSTEMS LABORATORY EE 354 COMMUNICATION SYSTEMS EXPERIMENT 3: SAMPLING & TIME DIVISION MULTIPLEX (TDM) Objective: Experimental verification of the

More information

Fundamentals of Digital Communication

Fundamentals of Digital Communication Fundamentals of Digital Communication Network Infrastructures A.A. 2017/18 Digital communication system Analog Digital Input Signal Analog/ Digital Low Pass Filter Sampler Quantizer Source Encoder Channel

More information

Principles of Baseband Digital Data Transmission

Principles of Baseband Digital Data Transmission Principles of Baseband Digital Data Transmission Prof. Wangrok Oh Dept. of Information Communications Eng. Chungnam National University Prof. Wangrok Oh(CNU) / 3 Overview Baseband Digital Data Transmission

More information

Department of Electronics & Telecommunication Engg. LAB MANUAL. B.Tech V Semester [ ] (Branch: ETE)

Department of Electronics & Telecommunication Engg. LAB MANUAL. B.Tech V Semester [ ] (Branch: ETE) Department of Electronics & Telecommunication Engg. LAB MANUAL SUBJECT:-DIGITAL COMMUNICATION SYSTEM [BTEC-501] B.Tech V Semester [2013-14] (Branch: ETE) KCT COLLEGE OF ENGG & TECH., FATEHGARH PUNJAB TECHNICAL

More information

Basic Concepts in Data Transmission

Basic Concepts in Data Transmission Basic Concepts in Data Transmission EE450: Introduction to Computer Networks Professor A. Zahid A.Zahid-EE450 1 Data and Signals Data is an entity that convey information Analog Continuous values within

More information

Emona Telecoms-Trainer ETT-101

Emona Telecoms-Trainer ETT-101 EXPERIMENTS IN MODERN COMMUNICATIONS Emona Telecoms-Trainer ETT-101 Multi-Experiment Single Board Telecommunications Trainer for Technical College and Technical High School Students EMONA INSTRUMENTS www.ett101.com

More information

LOOKING AT DATA SIGNALS

LOOKING AT DATA SIGNALS LOOKING AT DATA SIGNALS We diplay data signals graphically in many ways, ranging from textbook illustrations to test equipment screens. This note helps you integrate those views and to see how some modulation

More information

Handout 11: Digital Baseband Transmission

Handout 11: Digital Baseband Transmission ENGG 23-B: Principles of Communication Systems 27 8 First Term Handout : Digital Baseband Transmission Instructor: Wing-Kin Ma November 7, 27 Suggested Reading: Chapter 8 of Simon Haykin and Michael Moher,

More information

ITM 1010 Computer and Communication Technologies

ITM 1010 Computer and Communication Technologies ITM 1010 Computer and Communication Technologies Lecture #14 Part II Introduction to Communication Technologies: Digital Signals: Digital modulation, channel sharing 2003 香港中文大學, 電子工程學系 (Prof. H.K.Tsang)

More information

MODELLING AN EQUATION

MODELLING AN EQUATION MODELLING AN EQUATION PREPARATION...1 an equation to model...1 the ADDER...2 conditions for a null...3 more insight into the null...4 TIMS experiment procedures...5 EXPERIMENT...6 signal-to-noise ratio...11

More information

UNIT III -- DATA AND PULSE COMMUNICATION PART-A 1. State the sampling theorem for band-limited signals of finite energy. If a finite energy signal g(t) contains no frequency higher than W Hz, it is completely

More information

EEE 309 Communication Theory

EEE 309 Communication Theory EEE 309 Communication Theory Semester: January 2017 Dr. Md. Farhad Hossain Associate Professor Department of EEE, BUET Email: mfarhadhossain@eee.buet.ac.bd Office: ECE 331, ECE Building Types of Modulation

More information

Experiment Five: The Noisy Channel Model

Experiment Five: The Noisy Channel Model Experiment Five: The Noisy Channel Model Modified from original TIMS Manual experiment by Mr. Faisel Tubbal. Objectives 1) Study and understand the use of marco CHANNEL MODEL module to generate and add

More information

Communication Systems Lab

Communication Systems Lab LAB MANUAL Communication Systems Lab (EE-226-F) Prepared by: Varun Sharma (Lab In-charge) Dayal C. Sati (Faculty In-charge) B R C M CET BAHAL DEPARTMENT OF ELECTRONICS & COMMUNICATION ENGINEERING Page

More information

The Sampling Theorem:

The Sampling Theorem: The Sampling Theorem: Aim: Experimental verification of the sampling theorem; sampling and message reconstruction (interpolation). Experimental Procedure: Taking Samples: In the first part of the experiment

More information

EE 4440 Comm Theory Lab 5 Line Codes

EE 4440 Comm Theory Lab 5 Line Codes EE 4440 Comm Theory Lab 5 Line Codes Purpose: The purpose of this lab is to investigate the properties of various line codes. Specific parameters investigated will be wave shape, bandwidth, and transparency.

More information

DIGITAL COMMUNICATIONS LAB

DIGITAL COMMUNICATIONS LAB DIGITAL COMMUNICATIONS LAB List of Experiments: 1. PCM Generation and Detection. 2. Differential Pulse Code modulation. 3. Delta modulation. 4. Time Division Multiplexing of 2band Limited Signals. 5. Frequency

More information

Theory of Telecommunications Networks

Theory of Telecommunications Networks Theory of Telecommunications Networks Anton Čižmár Ján Papaj Department of electronics and multimedia telecommunications CONTENTS Preface... 5 1 Introduction... 6 1.1 Mathematical models for communication

More information

Sampling and Reconstruction

Sampling and Reconstruction Experiment 10 Sampling and Reconstruction In this experiment we shall learn how an analog signal can be sampled in the time domain and then how the same samples can be used to reconstruct the original

More information

EE-4022 Experiment 3 Frequency Modulation (FM)

EE-4022 Experiment 3 Frequency Modulation (FM) EE-4022 MILWAUKEE SCHOOL OF ENGINEERING 2015 Page 3-1 Student Objectives: EE-4022 Experiment 3 Frequency Modulation (FM) In this experiment the student will use laboratory modules including a Voltage-Controlled

More information

Digital Modulation Schemes

Digital Modulation Schemes Digital Modulation Schemes 1. In binary data transmission DPSK is preferred to PSK because (a) a coherent carrier is not required to be generated at the receiver (b) for a given energy per bit, the probability

More information

Class 4 ((Communication and Computer Networks))

Class 4 ((Communication and Computer Networks)) Class 4 ((Communication and Computer Networks)) Lesson 5... SIGNAL ENCODING TECHNIQUES Abstract Both analog and digital information can be encoded as either analog or digital signals. The particular encoding

More information

CSE 123: Computer Networks Alex C. Snoeren. Project 1 out Today, due 10/26!

CSE 123: Computer Networks Alex C. Snoeren. Project 1 out Today, due 10/26! CSE 123: Computer Networks Alex C. Snoeren Project 1 out Today, due 10/26! Signaling Types of physical media Shannon s Law and Nyquist Limit Encoding schemes Clock recovery Manchester, NRZ, NRZI, etc.

More information

18.8 Channel Capacity

18.8 Channel Capacity 674 COMMUNICATIONS SIGNAL PROCESSING 18.8 Channel Capacity The main challenge in designing the physical layer of a digital communications system is approaching the channel capacity. By channel capacity

More information

Practice 2. Baseband Communication

Practice 2. Baseband Communication PRACTICE : Practice. Baseband Communication.. Objectives To learn to use the software Simulink of MATLAB so as to analyze baseband communication systems... Practical development... Unipolar NRZ signal

More information

Signal Characteristics

Signal Characteristics Data Transmission The successful transmission of data depends upon two factors:» The quality of the transmission signal» The characteristics of the transmission medium Some type of transmission medium

More information

The quality of the transmission signal The characteristics of the transmission medium. Some type of transmission medium is required for transmission:

The quality of the transmission signal The characteristics of the transmission medium. Some type of transmission medium is required for transmission: Data Transmission The successful transmission of data depends upon two factors: The quality of the transmission signal The characteristics of the transmission medium Some type of transmission medium is

More information

Advanced Digital Signal Processing Part 2: Digital Processing of Continuous-Time Signals

Advanced Digital Signal Processing Part 2: Digital Processing of Continuous-Time Signals Advanced Digital Signal Processing Part 2: Digital Processing of Continuous-Time Signals Gerhard Schmidt Christian-Albrechts-Universität zu Kiel Faculty of Engineering Institute of Electrical Engineering

More information

Digital Communication - Pulse Shaping

Digital Communication - Pulse Shaping Digital Communication - Pulse Shaping After going through different types of coding techniques, we have an idea on how the data is prone to distortion and how the measures are taken to prevent it from

More information

Line Coding for Digital Communication

Line Coding for Digital Communication Line Coding for Digital Communication How do we transmit bits over a wire, RF, fiber? Line codes, many options Power spectrum of line codes, how much bandwidth do they take Clock signal and synchronization

More information

QUESTION BANK EC 1351 DIGITAL COMMUNICATION YEAR / SEM : III / VI UNIT I- PULSE MODULATION PART-A (2 Marks) 1. What is the purpose of sample and hold

QUESTION BANK EC 1351 DIGITAL COMMUNICATION YEAR / SEM : III / VI UNIT I- PULSE MODULATION PART-A (2 Marks) 1. What is the purpose of sample and hold QUESTION BANK EC 1351 DIGITAL COMMUNICATION YEAR / SEM : III / VI UNIT I- PULSE MODULATION PART-A (2 Marks) 1. What is the purpose of sample and hold circuit 2. What is the difference between natural sampling

More information

Exercise 3-2. Digital Modulation EXERCISE OBJECTIVE DISCUSSION OUTLINE DISCUSSION. PSK digital modulation

Exercise 3-2. Digital Modulation EXERCISE OBJECTIVE DISCUSSION OUTLINE DISCUSSION. PSK digital modulation Exercise 3-2 Digital Modulation EXERCISE OBJECTIVE When you have completed this exercise, you will be familiar with PSK digital modulation and with a typical QPSK modulator and demodulator. DISCUSSION

More information

Jitter in Digital Communication Systems, Part 1

Jitter in Digital Communication Systems, Part 1 Application Note: HFAN-4.0.3 Rev.; 04/08 Jitter in Digital Communication Systems, Part [Some parts of this application note first appeared in Electronic Engineering Times on August 27, 200, Issue 8.] AVAILABLE

More information

Digital signal is denoted by discreet signal, which represents digital data.there are three types of line coding schemes available:

Digital signal is denoted by discreet signal, which represents digital data.there are three types of line coding schemes available: Digital-to-Digital Conversion This section explains how to convert digital data into digital signals. It can be done in two ways, line coding and block coding. For all communications, line coding is necessary

More information

EXPERIMENT 1: Amplitude Shift Keying (ASK)

EXPERIMENT 1: Amplitude Shift Keying (ASK) EXPERIMENT 1: Amplitude Shift Keying (ASK) 1) OBJECTIVE Generation and demodulation of an amplitude shift keyed (ASK) signal 2) PRELIMINARY DISCUSSION In ASK, the amplitude of a carrier signal is modified

More information

COMPUTER COMMUNICATION AND NETWORKS ENCODING TECHNIQUES

COMPUTER COMMUNICATION AND NETWORKS ENCODING TECHNIQUES COMPUTER COMMUNICATION AND NETWORKS ENCODING TECHNIQUES Encoding Coding is the process of embedding clocks into a given data stream and producing a signal that can be transmitted over a selected medium.

More information

ECE 4600 Communication Systems

ECE 4600 Communication Systems ECE 4600 Communication Systems Dr. Bradley J. Bazuin Associate Professor Department of Electrical and Computer Engineering College of Engineering and Applied Sciences Course Topics Course Introduction

More information

Objectives. Presentation Outline. Digital Modulation Lecture 03

Objectives. Presentation Outline. Digital Modulation Lecture 03 Digital Modulation Lecture 03 Inter-Symbol Interference Power Spectral Density Richard Harris Objectives To be able to discuss Inter-Symbol Interference (ISI), its causes and possible remedies. To be able

More information

Problems from the 3 rd edition

Problems from the 3 rd edition (2.1-1) Find the energies of the signals: a) sin t, 0 t π b) sin t, 0 t π c) 2 sin t, 0 t π d) sin (t-2π), 2π t 4π Problems from the 3 rd edition Comment on the effect on energy of sign change, time shifting

More information

EEE 309 Communication Theory

EEE 309 Communication Theory EEE 309 Communication Theory Semester: January 2016 Dr. Md. Farhad Hossain Associate Professor Department of EEE, BUET Email: mfarhadhossain@eee.buet.ac.bd Office: ECE 331, ECE Building Part 05 Pulse Code

More information

Lecture 3: Modulation & Clock Recovery. CSE 123: Computer Networks Stefan Savage

Lecture 3: Modulation & Clock Recovery. CSE 123: Computer Networks Stefan Savage Lecture 3: Modulation & Clock Recovery CSE 123: Computer Networks Stefan Savage Lecture 3 Overview Signaling constraints Shannon s Law Nyquist Limit Encoding schemes Clock recovery Manchester, NRZ, NRZI,

More information

Introduction: Presence or absence of inherent error detection properties.

Introduction: Presence or absence of inherent error detection properties. Introduction: Binary data can be transmitted using a number of different types of pulses. The choice of a particular pair of pulses to represent the symbols 1 and 0 is called Line Coding and the choice

More information

Chapter 3 Digital Transmission Fundamentals

Chapter 3 Digital Transmission Fundamentals Chapter 3 Digital Transmission Fundamentals Characterization of Communication Channels Fundamental Limits in Digital Transmission CSE 323, Winter 200 Instructor: Foroohar Foroozan Chapter 3 Digital Transmission

More information

Lecture 3: Modulation & Clock Recovery. CSE 123: Computer Networks Alex C. Snoeren

Lecture 3: Modulation & Clock Recovery. CSE 123: Computer Networks Alex C. Snoeren Lecture 3: Modulation & Clock Recovery CSE 123: Computer Networks Alex C. Snoeren Lecture 3 Overview Signaling constraints Shannon s Law Nyquist Limit Encoding schemes Clock recovery Manchester, NRZ, NRZI,

More information

Costas Loop. Modules: Sequence Generator, Digital Utilities, VCO, Quadrature Utilities (2), Phase Shifter, Tuneable LPF (2), Multiplier

Costas Loop. Modules: Sequence Generator, Digital Utilities, VCO, Quadrature Utilities (2), Phase Shifter, Tuneable LPF (2), Multiplier Costas Loop Modules: Sequence Generator, Digital Utilities, VCO, Quadrature Utilities (2), Phase Shifter, Tuneable LPF (2), Multiplier 0 Pre-Laboratory Reading Phase-shift keying that employs two discrete

More information

CHAPTER 3 Syllabus (2006 scheme syllabus) Differential pulse code modulation DPCM transmitter

CHAPTER 3 Syllabus (2006 scheme syllabus) Differential pulse code modulation DPCM transmitter CHAPTER 3 Syllabus 1) DPCM 2) DM 3) Base band shaping for data tranmission 4) Discrete PAM signals 5) Power spectra of discrete PAM signal. 6) Applications (2006 scheme syllabus) Differential pulse code

More information

Course 2: Channels 1 1

Course 2: Channels 1 1 Course 2: Channels 1 1 "You see, wire telegraph is a kind of a very, very long cat. You pull his tail in New York and his head is meowing in Los Angeles. Do you understand this? And radio operates exactly

More information

ON SYMBOL TIMING RECOVERY IN ALL-DIGITAL RECEIVERS

ON SYMBOL TIMING RECOVERY IN ALL-DIGITAL RECEIVERS ON SYMBOL TIMING RECOVERY IN ALL-DIGITAL RECEIVERS 1 Ali A. Ghrayeb New Mexico State University, Box 30001, Dept 3-O, Las Cruces, NM, 88003 (e-mail: aghrayeb@nmsu.edu) ABSTRACT Sandia National Laboratories

More information

Chapter Two. Fundamentals of Data and Signals. Data Communications and Computer Networks: A Business User's Approach Seventh Edition

Chapter Two. Fundamentals of Data and Signals. Data Communications and Computer Networks: A Business User's Approach Seventh Edition Chapter Two Fundamentals of Data and Signals Data Communications and Computer Networks: A Business User's Approach Seventh Edition After reading this chapter, you should be able to: Distinguish between

More information

CHAPTER. delta-sigma modulators 1.0

CHAPTER. delta-sigma modulators 1.0 CHAPTER 1 CHAPTER Conventional delta-sigma modulators 1.0 This Chapter presents the traditional first- and second-order DSM. The main sources for non-ideal operation are described together with some commonly

More information

Revision of Wireless Channel

Revision of Wireless Channel Revision of Wireless Channel Quick recap system block diagram CODEC MODEM Wireless Channel Previous three lectures looked into wireless mobile channels To understand mobile communication technologies,

More information

Communications I (ELCN 306)

Communications I (ELCN 306) Communications I (ELCN 306) c Samy S. Soliman Electronics and Electrical Communications Engineering Department Cairo University, Egypt Email: samy.soliman@cu.edu.eg Website: http://scholar.cu.edu.eg/samysoliman

More information

UNIVERSITY OF NORTH CAROLINA AT CHARLOTTE Department of Electrical and Computer Engineering

UNIVERSITY OF NORTH CAROLINA AT CHARLOTTE Department of Electrical and Computer Engineering UNIVERSITY OF NORTH CAROLINA AT CHARLOTTE Department of Electrical and Computer Engineering EXPERIMENT 1 INTRODUCTION TO THE EMONA SIGEX BOARD FOR NI ELVIS OBJECTIVES The purpose of this experiment is

More information

Ș.l. dr. ing. Lucian-Florentin Bărbulescu

Ș.l. dr. ing. Lucian-Florentin Bărbulescu Ș.l. dr. ing. Lucian-Florentin Bărbulescu 1 Data: entities that convey meaning within a computer system Signals: are the electric or electromagnetic impulses used to encode and transmit data Characteristics

More information

Exploring QAM using LabView Simulation *

Exploring QAM using LabView Simulation * OpenStax-CNX module: m14499 1 Exploring QAM using LabView Simulation * Robert Kubichek This work is produced by OpenStax-CNX and licensed under the Creative Commons Attribution License 2.0 1 Exploring

More information

ADVANCED EXPERIMENTS IN MODERN COMMUNICATIONS

ADVANCED EXPERIMENTS IN MODERN COMMUNICATIONS ADVANCED EXPERIMENTS IN MODERN COMMUNICATIONS NEW FIBER OPTICS KIT New Generation Single-Board Telecoms Experimenter for Advanced Experiments Emona ETT-101 BiSKIT Multi-Experiment Telecommunications &

More information

CHAPTER 4. PULSE MODULATION Part 2

CHAPTER 4. PULSE MODULATION Part 2 CHAPTER 4 PULSE MODULATION Part 2 Pulse Modulation Analog pulse modulation: Sampling, i.e., information is transmitted only at discrete time instants. e.g. PAM, PPM and PDM Digital pulse modulation: Sampling

More information

Department of Communication Engineering Digital Communication Systems Lab CME 313-Lab

Department of Communication Engineering Digital Communication Systems Lab CME 313-Lab German Jordanian University Department of Communication Engineering Digital Communication Systems Lab CME 313-Lab Experiment 2 Pulse Modulation Eng. AnasAlashqar Dr. Ala' Khalifeh 1 Experiment 1Experiment

More information

Chapter 4 Digital Transmission 4.1

Chapter 4 Digital Transmission 4.1 Chapter 4 Digital Transmission 4.1 Copyright The McGraw-Hill Companies, Inc. Permission required for reproduction or display. 4-1 DIGITAL-TO-DIGITAL CONVERSION In this section, we see how we can represent

More information

DE63 DIGITAL COMMUNICATIONS DEC 2014

DE63 DIGITAL COMMUNICATIONS DEC 2014 Q.2 a. Draw the bandwidth efficiency curve w.r.t E b /N o. Compute the value of E b /N o required to achieve the data rate equal to the channel capacity if the channel bandwidth tends to infinity b. A

More information

Pulse-Width Modulation (PWM)

Pulse-Width Modulation (PWM) Pulse-Width Modulation (PWM) Modules: Integrate & Dump, Digital Utilities, Wideband True RMS Meter, Tuneable LPF, Audio Oscillator, Multiplier, Utilities, Noise Generator, Speech, Headphones. 0 Pre-Laboratory

More information

SEN366 Computer Networks

SEN366 Computer Networks SEN366 Computer Networks Prof. Dr. Hasan Hüseyin BALIK (5 th Week) 5. Signal Encoding Techniques 5.Outline An overview of the basic methods of encoding digital data into a digital signal An overview of

More information

MODELLING EQUATIONS. modules. preparation. an equation to model. basic: ADDER, AUDIO OSCILLATOR, PHASE SHIFTER optional basic: MULTIPLIER 1/10

MODELLING EQUATIONS. modules. preparation. an equation to model. basic: ADDER, AUDIO OSCILLATOR, PHASE SHIFTER optional basic: MULTIPLIER 1/10 MODELLING EQUATIONS modules basic: ADDER, AUDIO OSCILLATOR, PHASE SHIFTER optional basic: MULTIPLIER preparation This experiment assumes no prior knowledge of telecommunications. It illustrates how TIMS

More information

Chapter 2 Direct-Sequence Systems

Chapter 2 Direct-Sequence Systems Chapter 2 Direct-Sequence Systems A spread-spectrum signal is one with an extra modulation that expands the signal bandwidth greatly beyond what is required by the underlying coded-data modulation. Spread-spectrum

More information

Amplitude Modulation Methods and Circuits

Amplitude Modulation Methods and Circuits Amplitude Modulation Methods and Circuits By: Mark Porubsky Milwaukee Area Technical College Electronic Technology Electronic Communications Milwaukee, WI Purpose: The various parts of this lab unit will

More information

Chpater 8 Digital Transmission through Bandlimited AWGN Channels

Chpater 8 Digital Transmission through Bandlimited AWGN Channels Chapter 8. Digital Transmission through Bandlimited AWGN Channels - 1-1 st Semester, 008 Chpater 8 Digital Transmission through Bandlimited AWGN Channels Text. [1] J. G. Proakis and M. Salehi, Communication

More information

DEPARTMENT OF COMPUTER GCE@Bodi_ SCIENCE GCE@Bodi_ AND ENIGNEERING GCE@Bodi_ GCE@Bodi_ GCE@Bodi_ Analog and Digital Communication GCE@Bodi_ DEPARTMENT OF CsE Subject Name: Analog and Digital Communication

More information

AC LAB ECE-D ecestudy.wordpress.com

AC LAB ECE-D ecestudy.wordpress.com PART B EXPERIMENT NO: 1 AIM: PULSE AMPLITUDE MODULATION (PAM) & DEMODULATION DATE: To study Pulse Amplitude modulation and demodulation process with relevant waveforms. APPARATUS: 1. Pulse amplitude modulation

More information

Chapter 7: Pulse Modulation

Chapter 7: Pulse Modulation Generation of TDM-PAM signal (example) Input signals TDM-PAM signal f 2 f 1 f ( t 3 ) F 1 0 m F 2 F 3 is very complicated. 0 m Low-pass filter Impulse response Transmitted signal f4 = f3( t) hx F 4 = F3

More information

Outline. Communications Engineering 1

Outline. Communications Engineering 1 Outline Introduction Signal, random variable, random process and spectra Analog modulation Analog to digital conversion Digital transmission through baseband channels Signal space representation Optimal

More information

Data Communications & Computer Networks

Data Communications & Computer Networks Data Communications & Computer Networks Chapter 3 Data Transmission Fall 2008 Agenda Terminology and basic concepts Analog and Digital Data Transmission Transmission impairments Channel capacity Home Exercises

More information

UNIT I Source Coding Systems

UNIT I Source Coding Systems SIDDHARTH GROUP OF INSTITUTIONS: PUTTUR Siddharth Nagar, Narayanavanam Road 517583 QUESTION BANK (DESCRIPTIVE) Subject with Code: DC (16EC421) Year & Sem: III-B. Tech & II-Sem Course & Branch: B. Tech

More information

Digital frequency modulation as a technique for improving telemetry sampling bandwidth utilization

Digital frequency modulation as a technique for improving telemetry sampling bandwidth utilization Digital frequency modulation as a technique for improving telemetry sampling bandwidth utilization by G. E. HEYLGER Martin Marietta Corporation Denver, Colorado NTRODUCTON A hybrid of Time Division Multiplexing

More information

Step Response of RC Circuits

Step Response of RC Circuits EE 233 Laboratory-1 Step Response of RC Circuits 1 Objectives Measure the internal resistance of a signal source (eg an arbitrary waveform generator) Measure the output waveform of simple RC circuits excited

More information

: DIGITAL COMMUNICATION

: DIGITAL COMMUNICATION SRM UNIVERSITY FACULTY OF ENGINEERING AND TECHNOLOGY DEPARTMENT OF ECE COURSE PLAN Course Code : EC0307 Course Title : DIGITAL COMMUNICATION Semester : V Course Time : JULY NOVEMBER 2012 Location : S.R.M.TECH

More information

Waveform Encoding - PCM. BY: Dr.AHMED ALKHAYYAT. Chapter Two

Waveform Encoding - PCM. BY: Dr.AHMED ALKHAYYAT. Chapter Two Chapter Two Layout: 1. Introduction. 2. Pulse Code Modulation (PCM). 3. Differential Pulse Code Modulation (DPCM). 4. Delta modulation. 5. Adaptive delta modulation. 6. Sigma Delta Modulation (SDM). 7.

More information

Computer-Aided Analysis of Interference and Intermodulation Distortion in FDMA Data Transmission Systems

Computer-Aided Analysis of Interference and Intermodulation Distortion in FDMA Data Transmission Systems Computer-Aided Analysis of Interference and Intermodulation Distortion in FDMA Data Transmission Systems Item Type text; Proceedings Authors Balaban, P.; Shanmugam, K. S. Publisher International Foundation

More information

Digital modulation techniques

Digital modulation techniques Outline Introduction Signal, random variable, random process and spectra Analog modulation Analog to digital conversion Digital transmission through baseband channels Signal space representation Optimal

More information